Temperature dependence of parasitoid infection and abundance of a diatom revealed by automated imaging and classification.
Temperature dependence of parasitoid infection and abundance of a diatom revealed by automated imaging and classification.
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自动成像和分类揭示了寄生虫感染的温度依赖性和硅藻的丰度。
DOI：
10.1073/pnas.2303356120
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发表时间：
2023-07-11
影响因子：
11.1
通讯作者：
Sosik, Heidi M.
中科院分区：
文献类型：
--
作者：
Catlett, Dylan;Peacock, Emily E.;Crockford, E. Taylor;Futrelle, Joe;Batchelder, Sidney;Stevens, Bethany L. F.;Gast, Rebecca J.;Zhang, Weifeng G.;Sosik, Heidi M.
硅藻是单细胞藻类，其“水华”与高初级生产力、多产渔业和向深海的碳通量有关。尽管其对海洋食物网的潜在影响，硅藻寄生是知之甚少，由于在适当的时空尺度上观察其流行和环境控制的挑战。在这里，我们使用自动浮游生物成像和机器学习分类来阐明美国东北部大陆架（内斯）生物量占主导地位的硅藻的丰度和寄生虫感染动态。我们认为，温度间接调节硅藻丰度通过直接抑制寄生。这种温度依赖性意味着，持续变暖可能使寄生虫感染全年发生，推动这种硅藻的丰度动态的巨大变化与潜在的级联效应的内斯生态系统。硅藻是一组浮游植物，对全球初级生产的贡献不成比例。传统的模式，认为硅藻主要是由较大的浮游动物消耗的挑战，零星的寄生虫“流行病”的硅藻种群。然而，我们对硅藻寄生的理解受到量化这些相互作用的困难的限制。在这里，我们观察的动态Cryothecomonasaestivalis（原生生物）感染的一个重要的硅藻在美国东北部的货架（内斯），微妙的Guinardia，结合自动成像流式细胞术和卷积神经网络图像分类器。分类器的应用程序，从近岸时间序列和超过20个调查巡航更广泛的内斯超过10亿图像揭示了时空梯度和温度依赖性的G。delicatula丰度和感染动态。在<4 °C的温度下抑制寄生蜂感染驱动了两种G. delicatula感染和丰度，每年最大的感染观察到在秋冬之前，每年最大的主机丰富的冬春。这种年度周期可能在整个内斯的空间变化，以响应可变的年度周期的水温。我们发现，感染仍然抑制了约2个月后冷期，可能是由于温度引起的局部排斥的C。aestivalis菌株感染G. delicatula。这些发现对预测变暖的内斯海表对G. delicatula丰度和感染动态，并展示了自动浮游生物成像和分类的潜力，以量化浮游植物寄生在自然界中前所未有的时空尺度。
Diatoms are unicellular algae whose “blooms” are associated with high primary productivity, prolific fisheries, and carbon flux to the deep ocean. Despite its potential impact on marine food webs, diatom parasitism is poorly understood due to challenges observing its prevalence and environmental controls at appropriate spatiotemporal scales. Here, we use automated plankton imaging and machine learning classification to elucidate abundance and parasitic infection dynamics of a biomass-dominant diatom on the Northeast U.S. Shelf (NES). We suggest that temperature indirectly regulates diatom abundance via direct suppression of parasitism. This temperature dependence implies that ongoing warming may enable parasitic infection to occur throughout the year, driving dramatic shifts in this diatom’s abundance dynamics with potential cascading effects on the NES ecosystem. Diatoms are a group of phytoplankton that contribute disproportionately to global primary production. Traditional paradigms that suggest diatoms are consumed primarily by larger zooplankton are challenged by sporadic parasitic “epidemics” within diatom populations. However, our understanding of diatom parasitism is limited by difficulties in quantifying these interactions. Here, we observe the dynamics of Cryothecomonas aestivalis (a protist) infection of an important diatom on the Northeast U.S. Shelf (NES), Guinardia delicatula, with a combination of automated imaging-in-flow cytometry and a convolutional neural network image classifier. Application of the classifier to >1 billion images from a nearshore time series and >20 survey cruises across the broader NES reveals the spatiotemporal gradients and temperature dependence of G. delicatula abundance and infection dynamics. Suppression of parasitoid infection at temperatures <4 °C drives annual cycles in both G. delicatula infection and abundance, with an annual maximum in infection observed in the fall-winter preceding an annual maximum in host abundance in the winter-spring. This annual cycle likely varies spatially across the NES in response to variable annual cycles in water temperature. We show that infection remains suppressed for ~2 mo following cold periods, possibly due to temperature-induced local extinctions of the C. aestivalis strain(s) that infect G. delicatula. These findings have implications for predicting impacts of a warming NES surface ocean on G. delicatula abundance and infection dynamics and demonstrate the potential of automated plankton imaging and classification to quantify phytoplankton parasitism in nature across unprecedented spatiotemporal scales.
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影响因子：
2.1
作者：
Gonzalez, Pablo;Castano, Alberto;Sosik, Heidi M.
通讯作者：
Sosik, Heidi M.
影响因子：
5.2
作者：
Barber, R. T.;Hiscock, M. R.
通讯作者：
Hiscock, M. R.
影响因子：
48
作者：
Callahan BJ;McMurdie PJ;Rosen MJ;Han AW;Johnson AJ;Holmes SP
通讯作者：
Holmes SP
影响因子：
56.9
作者：
Lima-Mendez, Gipsi;Faust, Karoline;Wincker, Patrick
通讯作者：
Wincker, Patrick
影响因子：
5.2
作者：
Chen, Zhuomin;Kwon, Young-Oh;Joyce, Terrence M.
通讯作者：
Joyce, Terrence M.