Mathers Andrew W, Hepworth Christopher, Baillie Alice L, Sloan Jen, Jones Hannah, Lundgren Marjorie, Fleming Andrew J, Mooney Sacha J, Sturrock Craig J
1Division of Agricultural and Environmental Sciences, School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough, Leicestershire LE12 5RD UK.
2Department of Animal and Plant Sciences, University of Sheffield, Western Bank, Sheffield, S10 2TN UK.
Plant Methods. 2018 Nov 12;14:99. doi: 10.1186/s13007-018-0367-7. eCollection 2018.
Leaf cellular architecture plays an important role in setting limits for carbon assimilation and, thus, photosynthetic performance. However, the low density, fine structure, and sensitivity to desiccation of plant tissue has presented challenges to its quantification. Classical methods of tissue fixation and embedding prior to 2D microscopy of sections is both laborious and susceptible to artefacts that can skew the values obtained. Here we report an image analysis pipeline that provides quantitative descriptors of plant leaf intercellular airspace using lab-based X-ray computed tomography (microCT). We demonstrate successful visualisation and quantification of differences in leaf intercellular airspace in 3D for a range of species (including both dicots and monocots) and provide a comparison with a standard 2D analysis of leaf sections.
We used the microCT image pipeline to obtain estimates of leaf porosity and mesophyll exposed surface area (S) for three dicot species (Arabidopsis, tomato and pea) and three monocot grasses (barley, oat and rice). The imaging pipeline consisted of (1) a masking operation to remove the background airspace surrounding the leaf, (2) segmentation by an automated threshold in ImageJ and then (3) quantification of the extracted pores using the ImageJ 'Analyze Particles' tool. Arabidopsis had the highest porosity and lowest S for the dicot species whereas barley had the highest porosity and the highest S for the grass species. Comparison of porosity and S estimates from 3D microCT analysis and 2D analysis of sections indicates that both methods provide a comparable estimate of porosity but the 2D method may underestimate S by almost 50%. A deeper study of porosity revealed similarities and differences in the asymmetric distribution of airspace between the species analysed.
Our results demonstrate the utility of high resolution imaging of leaf intercellular airspace networks by lab-based microCT and provide quantitative data on descriptors of leaf cellular architecture. They indicate there is a range of porosity and S values in different species and that there is not a simple relationship between these parameters, suggesting the importance of cell size, shape and packing in the determination of cellular parameters proposed to influence leaf photosynthetic performance.
叶片细胞结构在限制碳同化从而影响光合性能方面起着重要作用。然而，植物组织密度低、结构精细且对干燥敏感，这给其量化带来了挑战。传统的在对切片进行二维显微镜观察之前进行组织固定和包埋的方法既费力又容易产生假象，从而可能使获得的值出现偏差。在此，我们报告了一种图像分析流程，该流程使用基于实验室的X射线计算机断层扫描（显微CT）提供植物叶片细胞间隙的定量描述符。我们展示了对一系列物种（包括双子叶植物和单子叶植物）叶片细胞间隙差异进行成功的三维可视化和量化，并与叶片切片的标准二维分析进行了比较。
我们使用显微CT图像流程获得了三种双子叶植物（拟南芥、番茄和豌豆）和三种单子叶禾本科植物（大麦、燕麦和水稻）的叶片孔隙率和叶肉暴露表面积（S）的估计值。成像流程包括：（1）一个掩膜操作，以去除叶片周围的背景空隙；（2）在ImageJ中通过自动阈值进行分割，然后（3）使用ImageJ的“分析粒子”工具对提取的孔隙进行量化。对于双子叶植物物种，拟南芥的孔隙率最高，S最低；而对于禾本科植物物种，大麦的孔隙率最高，S也最高。三维显微CT分析和切片二维分析的孔隙率和S估计值比较表明，两种方法提供的孔隙率估计值具有可比性，但二维方法可能会使S低估近50%。对孔隙率的深入研究揭示了所分析物种之间细胞间隙不对称分布的异同。
我们的结果证明了基于实验室的显微CT对叶片细胞间隙网络进行高分辨率成像的实用性，并提供了叶片细胞结构描述符的定量数据。结果表明不同物种的孔隙率和S值存在一定范围，且这些参数之间不存在简单的关系，这表明细胞大小、形状和排列在决定被认为影响叶片光合性能的细胞参数方面具有重要性。
