养殖牡蛎死亡率随弧菌群落重组而持续上升。

IF 4.6 2区 生物学 Q1 MICROBIOLOGY
mSystems Pub Date : 2025-10-02 DOI:10.1128/msystems.01078-25
Steph Smith, Mark Ciesielski, Thomas Clerkin, Tal Ben-Horin, Rachel T Noble
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引用次数: 0

摘要

海洋双壳类动物的死亡事件给水产养殖造成了巨大的经济损失,但这些事件背后的微生物动力学特征仍然很差。在这里,我们调查了死亡事件期间牡蛎相关弧菌群落的演代模式,通过采样北卡罗莱纳商业养殖场的东部牡蛎(Crassostrea virginica),该养殖场经历了反复的、无法解释的死亡事件。通过对连续两年的死亡事件中从26只牡蛎中提取的110株弧菌进行全基因组测序,我们确定了6个具有不同时间关联的保守系统发育分支。在死亡开始时,地中海弧菌和一种常住弧菌一直在最初的培养群落中占主导地位。然而,随着死亡率的增加,地中海弧菌没有出现,与此同时,哈维弧菌、溶藻弧菌、暗黑弧菌和抗藻弧菌的丰度增加。比较基因组分析显示,初始分离株在与宿主定植和复杂碳代谢相关的途径中富集,而来自高死亡率的分离株在毒力机制和对降解宿主组织的适应方面富集。在遗传上不同的进化枝之间的时间分离表明,在死亡事件中,微生物的竞争塑造了群落的聚集,最终在这两年中死亡率都达到了85%。这种可预测的从共生到潜在致病性弧菌物种的演替提供了基因组水平上对牡蛎死亡期间微生物群落动态的洞察。地中海贝类在严重死亡之前的持续损失表明,该物种可以作为早期预警系统的生物指标,以减轻贝类养殖业的经济损失。水产养殖系统中的死亡事件代表了复杂的宿主-微生物-环境相互作用,挑战了我们预测和预防疾病的能力。通过在全基因组分辨率下表征牡蛎相关弧菌群落的演替模式,我们揭示了随着死亡的进展,从与健康牡蛎相关的代谢多样的物种到功能独特的弧菌类群的一致转变,这些弧菌类群富含毒力因子和组织降解途径。这种可预测群落重组的基因组水平证据表明,与仅追踪已知病原体相比,监测共生弧菌种群,特别是地中海弧菌的存在或缺失,可以提供即将发生疾病的早期预警。这种监测方法的转变可以促进水产养殖疾病管理,同时扩大我们对微生物群落转变如何促进宿主健康和疾病进展的基本理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Farmed oyster mortality follows consistent Vibrio community reorganization.

Mortality events in marine bivalves cause substantial economic losses in aquaculture, yet the microbial dynamics underlying these events remain poorly characterized. Here, we investigated succession patterns in oyster-associated Vibrio communities during mortality events by sampling eastern oysters (Crassostrea virginica) at a North Carolina commercial farm that has experienced repeated, unexplained mortality events. Through whole-genome sequencing of 110 Vibrio isolates from 26 oysters sampled across mortality events in two consecutive years, we identified six conserved phylogenetic clades with distinct temporal associations. Vibrio mediterranei and a clade of resident vibrios consistently dominated the initial cultured community at the onset of mortality. However, V. mediterranei was absent as mortality progressed, coinciding with increased abundance of V. harveyi, V. alginolyticus, V. diabolicus, and V. agarivorans. Comparative genomic analysis revealed that initial isolates were enriched in pathways associated with host colonization and complex carbon metabolism, while isolates from elevated mortality showed enrichment in virulence mechanisms and adaptation to degraded host tissues. Temporal separation between genetically distinct clades suggests microbial competition shapes community assembly during mortality events that ultimately reached >85% mortality in both years. This predictable succession from commensal to potentially pathogenic Vibrio species provides genome-level insight into microbial community dynamics during oyster mortality. The consistent loss of V. mediterranei prior to severe mortality suggests this species could serve as a bioindicator for early warning systems to mitigate economic losses in shellfish aquaculture.IMPORTANCEMortality events in aquaculture systems represent complex host-microbe-environment interactions that challenge our ability to predict and prevent disease. By characterizing succession patterns in oyster-associated Vibrio communities at whole-genome resolution, we reveal a consistent transition from metabolically versatile species associated with healthy oysters to functionally distinct Vibrio taxa enriched in virulence factors and tissue degradation pathways as mortality progresses. This genome-level evidence for predictable community reorganization suggests that monitoring commensal Vibrio populations, particularly the presence or absence of Vibrio mediterranei, could provide earlier warning of impending disease compared to tracking only known pathogens. This shift in monitoring approach could advance aquaculture disease management while expanding our fundamental understanding of how microbial community transitions contribute to host health and disease progression.

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来源期刊
mSystems
mSystems Biochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
10.50
自引率
3.10%
发文量
308
审稿时长
13 weeks
期刊介绍: mSystems™ will publish preeminent work that stems from applying technologies for high-throughput analyses to achieve insights into the metabolic and regulatory systems at the scale of both the single cell and microbial communities. The scope of mSystems™ encompasses all important biological and biochemical findings drawn from analyses of large data sets, as well as new computational approaches for deriving these insights. mSystems™ will welcome submissions from researchers who focus on the microbiome, genomics, metagenomics, transcriptomics, metabolomics, proteomics, glycomics, bioinformatics, and computational microbiology. mSystems™ will provide streamlined decisions, while carrying on ASM''s tradition of rigorous peer review.
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