A low-cost and open-source solution to automate imaging and analysis of cyst nematode infection assays for Arabidopsis thaliana

A low-cost and open-source solution to automate imaging and analysis of cyst nematode infection assays for Arabidopsis thaliana
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一种低成本开源解决方案,用于对拟南芥胞囊线虫感染检测进行自动化成像和分析

DOI:
10.1101/2022.07.14.500020
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发表时间:
2022
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通讯作者:
Kranse O
Kranse O
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作者:
Kranse O

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孢囊线虫是植物寄生线虫的主要类群之一,在世界范围内造成了严重的农作物损失。改良遗传资源,从而改良抗性品种,是许多害虫管理战略的持续重点。鉴定影响感染并因此影响产量的植物基因的主要瓶颈之一是表型。目前可用的筛选方法是缓慢的,具有一维量化的感染限制了可评分参数的范围,并且不考虑宿主的表型变异。不断发展的计算机视觉领域可能是上述问题的解决方案。要利用这些工具,需要一个专门的成像平台,采取一致的图像线虫感染在快速success.ResultsHere,我们描述了一个开源的,易于采用,成像硬件和性状分析软件方法的基础上预先存在的线虫感染筛选方法在无菌培养。开发了一种具有成本效益,易于构建和使用的3D打印成像设备,以获取感染胞囊线虫Heterodera schachtii的拟南芥根系的图像,取代昂贵的显微镜设备。将该设备的输出与简单的分析脚本相结合,可以以半自动化的方式从收集的图像中测量一些关键性状,如线虫数量和大小。此外,我们使用这种组合的解决方案来量化一个额外的性状,感染前的根面积,并显示了这一性状对线虫感染的混淆关系和一种方法来解释它。以及解释宿主表型变异的方法。这些工具一起突出了帮助我们理解线虫寄生的巨大潜力。
BackgroundCyst nematodes are one of the major groups of plant-parasitic nematode, responsible for considerable crop losses worldwide. Improving genetic resources, and therefore resistant cultivars, is an ongoing focus of many pest management strategies. One of the major bottlenecks in identifying the plant genes that impact the infection, and thus the yield, is phenotyping. The current available screening method is slow, has unidimensional quantification of infection limiting the range of scorable parameters, and does not account for phenotypic variation of the host. The ever-evolving field of computer vision may be the solution for both the above-mentioned issues. To utilise these tools, a specialised imaging platform is required to take consistent images of nematode infection in quick succession.ResultsHere, we describe an open-source, easy to adopt, imaging hardware and trait analysis software method based on a pre-existing nematode infection screening method in axenic culture. A cost-effective, easy-to-build and -use, 3D-printed imaging device was developed to acquire images of the root system ofArabidopsis thalianainfected with the cyst nematodeHeterodera schachtii, replacing costly microscopy equipment. Coupling the output of this device to simple analysis scripts allowed the measurement of some key traits such as nematode number and size from collected images, in a semi-automated manner. Additionally, we used this combined solution to quantify an additional trait, root area before infection, and showed both the confounding relationship of this trait on nematode infection and a method to account for it.ConclusionTaken together, this manuscript provides a low-cost and open-source method for nematode phenotyping that includes the biologically relevant nematode size as a scorable parameter, and a method to account for phenotypic variation of the host. Together these tools highlight great potential in aiding our understanding of nematode parasitism.
“苯托物”是一种柔性,自动化的开源植物表型解决方案。
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