It is now recognized that some diseases of aquatic animals are attributed to polymicrobial pathogens infection. Thus, the traditional view of "one pathogen, one disease" might mislead the identification of multiple pathogens, which in turn impedes the design of probiotics. To address this gap, we explored polymicrobial pathogens based on the origin and timing of increased abundance over shrimp white feces syndrome (WFS) progression. OTU70848 Vibrio fluvialis, OTU35090 V. coralliilyticus, and OTU28721 V. tubiashii were identified as the primary colonizers, whose abundances increased only in individuals that eventually showed disease signs but were stable in healthy subjects over the same timeframe. Notably, the random Forest model revealed that the profiles of the three primary colonizers contributed an overall 91.4% of diagnosing accuracy of shrimp health status. Additionally, NetShift analysis quantified that the three primary colonizers were important "drivers" in the gut microbiotas from healthy to WFS shrimp. For these reasons, the primary colonizers were potential pathogens that contributed to the exacerbation of WFS. By this logic, we further identified a few "drivers" commensals in healthy individuals, such as OUT50531 Demequina sediminicola and OTU_74495 Ruegeria lacuscaerulensis, which directly antagonized the three primary colonizers. The predicted functional pathways involved in energy metabolism, genetic information processing, terpenoids and polyketides metabolism, lipid and amino acid metabolism significantly decreased in diseased shrimp compared with those in healthy cohorts, in concordant with the knowledge that the attenuations of these functional pathways increase shrimp sensitivity to pathogen infection. Collectively, we provide an ecological framework for inferring polymicrobial pathogens and designing antagonized probiotics by quantifying their changed "driver" feature that intimately links shrimp WFS progression. This approach might generalize to the exploring disease etiology for other aquatic animals.

中文翻译：

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识别潜在的微生物病原体：超越差异丰度转向驾驶员分类群。

现在已经认识到，某些水生动物疾病归因于微生物病原体的感染。因此，传统的“一种病原体，一种疾病”的观点可能会误导多种病原体的鉴定，从而阻碍了益生菌的设计。为了解决这一差距，我们根据虾白粪综合征（WFS）进展中丰度增加的起源和时机，探索了多种微生物病原体。OTU70848病毒弧菌，OTU35090珊瑚溶血弧菌和OTU28721 V.tubiashii被鉴定为主要定居者，其丰度仅在最终显示出疾病迹象但在同一时间段内在健康受试者中稳定的个体中增加。值得注意的是，随机森林模型显示，这三个主要定殖者的特征总共贡献了91个。对虾健康状况的诊断准确性为4％。另外，NetShift分析量化了从健康虾到WFS虾的肠道菌群中的三个主要定植者是重要的“驱动器”。由于这些原因，主要定居者是导致WFS恶化的潜在病原体。通过这种逻辑，我们进一步确定了健康个体中的一些“推动者”奖赏，例如直接拮抗这三个主要定殖者的OUT50531 Demequina sediminicola和OTU_74495 Ruegeria lacuscaerulensis。与健康人群相比，患病虾的能量代谢，遗传信息处理，萜类化合物和聚酮化合物代谢，脂质和氨基酸代谢中涉及的预测功能途径明显减少，与这些功能途径的减弱增加了虾对病原体感染的敏感性相一致的认识。总的来说，我们提供了一个生态系统框架，用于通过推断其改变的“驱动程序”功能（与虾的WFS进程密切相关），推断出微生物的病原体并设计拮抗的益生菌。这种方法可能会推广到探索其他水生动物的疾病病因。