Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, OX2 6GG, UK.
Graduate School of Mathematical Sciences, The University of Tokyo, Tokyo, 153-8914, Japan.
Sci Rep. 2019 Mar 21;9(1):5015. doi: 10.1038/s41598-019-41459-9.
Ubiquitous in eukaryotic organisms, the flagellum is a well-studied organelle that is well-known to be responsible for motility in a variety of organisms. Commonly necessitated in their study is the capability to image and subsequently track the movement of one or more flagella using videomicroscopy, requiring digital isolation and location of the flagellum within a sequence of frames. Such a process in general currently requires some researcher input, providing some manual estimate or reliance on an experiment-specific heuristic to correctly identify and track the motion of a flagellum. Here we present a fully-automated method of flagellum identification from videomicroscopy based on the fact that the flagella are of approximately constant width when viewed by microscopy. We demonstrate the effectiveness of the algorithm by application to captured videomicroscopy of Leishmania mexicana, a parasitic monoflagellate of the family Trypanosomatidae. ImageJ Macros for flagellar identification are provided, and high accuracy and remarkable throughput are achieved via this unsupervised method, obtaining results comparable in quality to previous studies of closely-related species but achieved without the need for precursory measurements or the development of a specialised heuristic, enabling in general the automated generation of digitised kinematic descriptions of flagellar beating from videomicroscopy.
鞭毛在真核生物中普遍存在,是一种研究得很好的细胞器,其运动功能在各种生物中广为人知。在研究中,通常需要使用视频显微镜对一个或多个鞭毛进行成像和跟踪,这需要数字隔离,并在一系列帧中定位鞭毛。这个过程通常需要一些研究人员的输入,提供一些手动估计或依赖于特定于实验的启发式方法来正确识别和跟踪鞭毛的运动。在这里,我们提出了一种基于鞭毛在显微镜下的宽度基本保持不变的事实的全自动鞭毛识别方法。我们通过对寄生性鞭毛虫 Leishmania mexicana 的捕获视频显微镜的应用,证明了该算法的有效性。我们提供了用于鞭毛识别的 ImageJ 宏,并且通过这种无监督的方法实现了高精度和高吞吐量,获得的结果与之前对密切相关物种的研究质量相当,但无需进行预先测量或开发专门的启发式方法,从而能够普遍实现从视频显微镜自动生成鞭毛运动的数字化运动描述。