Helmholtz-Centre for Environmental Research - UFZ, Department Physiological Diversity, Permoserstraße 15, 04318, Leipzig, Germany.
German Centre for Integrative Biodiversity Research - iDiv, Department Physiological Diversity, Deutscher Platz 5e, 04318, Leipzig, Germany.
Cytometry A. 2019 Aug;95(8):854-868. doi: 10.1002/cyto.a.23870. Epub 2019 Aug 6.
Phytoplankton are aquatic, microscopically small primary producers, accounting for almost half of the worldwide carbon fixation. As early indicators of environmental change, they play a crucial role in water quality management. Human activities like climate change, eutrophication, or international shipping traffic strongly impact diversity of these organisms. Phytoplankton monitoring is a crucial step in the recognition of changes in community composition. The common standard for monitoring programs is manual microscopic counting, which strongly limits sample number and sampling frequency. In contrast, high-throughput technologies like standard flow cytometry (FCM) are restricted to a low taxonomic resolution, which makes them unsuitable for the identification of indicator species. Imaging flow cytometers (IFC) could overcome these limitations as they combine microscopy and high-throughput analysis. In comparison to single fluorescence values, image information not only allows for a wide variety of possibilities to characterize different species as well as immediate and fast measurements but also provides an archivable data output. Taxonomic resolution of IFC (ImageStream X Mk II) was proven comparable to standard FCM (FACSAria II) by the help of numerical evaluations. This is demonstrated on different levels of taxonomic differentiation of laboratory grown cultures in this study. Phytoplankton species discrimination by an imaging flow cytometer could be useful as supportive tool to make machine-learning classifications more robust, reliable, and flexible. Furthermore, this study provides examples, demonstrating the possibility of discrimination between species with similar fluorescence properties, strains, and even subpopulations. In contrast to standard FCM, each cell is not only represented as a dot in a cytogram but is also linked to microscopic brightfield and the author presents a new way to visualize this as image-based cytograms. The source code is supplied and could be useful for all kind of IFC data in general. © 2019 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.
浮游植物是水生的、微观的初级生产者，占全球碳固定量的近一半。作为环境变化的早期指标，它们在水质管理中起着至关重要的作用。气候变化、富营养化或国际航运交通等人类活动强烈影响着这些生物的多样性。浮游植物监测是识别群落组成变化的关键步骤。监测计划的常用标准是手动显微镜计数，这强烈限制了样本数量和采样频率。相比之下，高通量技术，如标准流式细胞术（FCM），其分类分辨率较低，因此不适合鉴定指示物种。成像流式细胞仪（IFC）可以克服这些限制，因为它们将显微镜和高通量分析结合在一起。与单个荧光值相比，图像信息不仅允许对不同物种进行广泛的特征描述以及即时和快速的测量，还提供了可存档的数据输出。通过数值评估，证明了 IFC（ImageStream X Mk II）的分类分辨率与标准 FCM（FACSAria II）相当。本研究通过不同实验室培养的浮游植物分类差异水平证明了这一点。通过成像流式细胞仪对浮游植物物种进行区分，可能有助于使机器学习分类更加稳健、可靠和灵活。此外，本研究还提供了一些示例，展示了区分具有相似荧光特性、菌株甚至亚群的物种的可能性。与标准 FCM 不同，每个细胞不仅在细胞图中表示为一个点，而且还与明场显微镜相关联，作者提出了一种新的方法将其可视化作为基于图像的细胞图。提供了源代码，可用于一般的所有类型的 IFC 数据。© 2019 作者。流式细胞术部分由 Wiley 期刊出版公司代表国际细胞分析协会出版。
