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Well-fed or nearly dead? Using quantitative PCR to detect dietary stress in Daphnia pulex.

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Figshare2023-03-31 更新2026-04-08 收录
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Nutrition is at the center of interactions between organisms and their environment. During this time of unprecedented anthropogenic environmental change, biological indicators of nutritional changes and their effects on ecosystems are crucial if we are to understand and mitigate these changes. In this study, we developed a qPCR assay to examine nutritional responsiveness of ten genes identified as potential indicators of nutritional state in the freshwater zooplankton <em>Daphnia pulex</em>. We grew animals in six ecologically relevant treatments: nutrient replete, low carbon (food), low phosphorus, low nitrogen, low calcium, and high Cyanobacteria. We selected ten nutrient sensitive genes, two per limiting nutrient, and two reference genes from an RNA sequencing dataset. We found that using the nutrient-specific pairs of genes for single nutrient limitation assays showed mixed results with some treatments (calcium, nitrogen, carbon) with high levels of treatment discrimination, but gene responses designed for other treatments (phosphorus and Cyanobacteria) showed little to no treatment discrimination. However, when we used all ten genes as a single nutritional state assay, we could discriminate between our six nutritional states with high levels of accuracy. These results represent a compelling proof of concept for the use of gene-based nutritional biomarkers, paving the way for the use of genetically based nutritional state biomarkers in the study of ecology

营养是生物与环境间相互作用的核心环节。在当前史无前例的人为环境变化时期,若要理解并缓解此类变化,营养变化的生物指示物及其对生态系统的影响至关重要。本研究开发了一套qPCR(实时定量聚合酶链反应)检测方法,用以探究淡水浮游动物蚤状溞(*Daphnia pulex*)中10个被鉴定为营养状态潜在指示物的基因的营养响应特性。我们在6种具有生态相关性的处理组中培养实验动物:营养充足组、低碳(食物)组、低磷组、低氮组、低钙组以及高蓝藻组。我们从RNA测序(RNA-seq)数据集中筛选出10个营养敏感基因(每种限制性营养元素对应2个),同时选取2个内参基因。研究发现,针对单一营养限制实验使用营养特异性基因对时,结果存在差异:部分处理组(钙、氮、碳)的处理组区分度较高,但针对其他处理组(磷与蓝藻)设计的基因响应指标几乎无法区分处理组。不过,当我们将全部10个基因整合为一套统一的营养状态检测方法时,能够以较高精度区分6种营养状态。本研究结果为基于基因的营养生物标志物的应用提供了极具说服力的概念验证,为基于基因的营养状态生物标志物在生态学研究中的应用铺平了道路。

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2023-03-31
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