eXtra Botany VIEWPOINT
Seeing space: visualization and quantification of plant leaf structure using X-ray micro-computed tomography R. Pajor1, A. Fleming2, C. P. Osborne2, S. A. Rolfe2, C. J. Sturrock1 and S. J. Mooney1,* 1
Sutton Bonington Campus, University of Nottingham, Leicestershire, LE12 5RD, UK 2 Department of Animal and Plant Sciences, University of Sheffield, Western Bank, Sheffield, S10 2TN, UK * To whom correspondence should be addressed. E-mail:
[email protected] Journal of Experimental Botany Vol. 64, No. 2, 385–390, 2013 doi:10.1093/jxb/ers392
Introduction A mechanistic understanding of plant physiological processes occurring in the above-ground organs, such as photosynthesis in leaves, requires knowledge of the structural properties of the tissues, including leaf thickness (Hanba et al., 1999; Zhu et al., 2010; Niinemets et al., 2011), cell size, and stomatal distribution influencing gas exchange (Sage and Sage, 2009; Gong et al., 2011; Terashima et al., 2011). However, previous work has been unable to determine precisely how the three dimensional (3D) complexity of leaf structure impacts upon photosynthetic activity, partly due to a lack of appropriate methods for undisturbed visualization and quantification of inner structures at an appropriate high resolution (i.e. 5–10 µm). Although there is a wide range of traditional, optical-based techniques for visualization and quantification of plant morphology and anatomy, ranging from imaging of thin sections to confocal microscopy of intact specimens, their use is usually limited by the type and size of sample material. Furthermore, analysis is often time consuming, destructive, and constrained to two dimensions (2D) (classical histology) or limited in optical depth (confocal microscopy).
Current imaging approaches for visualization of plant tissues Traditional light microscopy, such as confocal microscopy, is limited by the size and transparency of the sample. In addition,
only 2D information is obtained, meaning that serial sectioning of material is required prior to reconstructing anatomy in 3D. In addition, confocal microscopy often requires the use of highly refractive staining agents to enhance the contrast (Truernit et al., 2008). Confocal microscopy permits resolution to a cellular or subcellular level, but this technique is limited by the thickness of the specimen – usually up to 1 mm depending on transparency of the material. An alternative method to traditional light microscopy is optical projection tomography (OPT). OPT operates under similar principles to another increasingly popular form of imaging called X-ray Computed Tomography (CT). OPT obtains the 3D structure of a sample by collecting crosssectional images from different angles but uses visible photons rather than X-rays. OPT allows structural data of small, typically 1–10 mm samples, to be captured in 3D at a spatial resolution down to 5 µm (Sharpe, 2004). For example, Lee et al. (2006) showed how OPT can be used to visualize morphology, internal structure, and gene expression in Arabidopsis. Images can be obtained using either UV (tracing gene expression) or visible light (structural data) illumination of the sample from different angles. Light absorption is used to derive structural information. Despite the ability to generate 3D datasets, OPT (in common with most optical approaches) is limited in the thickness and size of the sample that can be analysed and also requires sample preparation and staining. More recently, non-invasive imaging techniques, such as Positron Emission Tomography (PET) and Magnetic Resonance Imaging (MRI) have been employed to acquire structural data in 3D. PET scanning relies on visualizing the distribution of short life radioactive tracers, such as carbon isotopes used in plant metabolic processes (Garbout et al., 2011). PET scanners detect the radiation generated during a decay of tracers in the sample which can be interpolated with structural data obtained by other techniques (i.e. computed tomography). Despite being a sensitive method, allowing detection of vestigial amounts of a tracer, PET is currently limited to a coarse resolution, ranging 1–5 mm. MRI produces datasets at a higher resolution (c.50 µm), however the differentiation between the structures of the tissue depends differences in their water content, which can be limiting. MRI uses radio waves interacting with protons alignment to create a number of images, which are then reconstructed into 3D volume representing the sample. Although both PET and MRI are capable of delivering structural information on plant tissues, they are more suited for studies related to physiological processes such as exploring water content/ transport (MRI) and C assimilation (PET) in plant tissues (Dhondt et al., 2010).
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Development of X-ray micro-CT and implications for plant related studies X-ray CT has evolved primarily from advances in the medical sciences and is now considered as an established tool for non-invasive, non-destructive, precise visualization and quantification of the internal structures of materials in 3D. In fact, recent work has reported the use of X-ray micro-CT for 4D imaging (with time) of plant root growth reflecting technological advances in scan times (Tracy et al., 2012). The imaging process in CT is based on the differential attenuation of X-rays in relation to the atomic number and specific density of the tissue (i.e. the beam passes more easily through lowdensity, low-atomic-number materials, whereas dense objects absorb or reflect the beam). Most commercially available systems use a high-energy X-ray source which generates a beam that passes through the sample mounted on a turntable stage. Changes in X-ray intensity are recorded on a digital detector and subsequently converted into 2D radiographs. The number of collected radiographs per scan differs subject to various conditions such as the desired resolution, duration of the scan, and size of the sample but is typically in the order of 1000. In the next step, the collected radiographs are reconstructed into 3D volumes for image analysis. The resolution of datasets acquired with X-ray CT depends on a number of factors, such the spot size of the X-ray gun, the geometric magnification of the system, detector size, and the size of the sample. Significant advances in X-ray gun design, detector technology, and optical-based X-ray beam focusing has led to many current systems providing submicron resolution (Hsieh, 2009; Van den Bulcke et al., 2009). In recent years, X-ray CT has been widely utilized in rhizosphere studies, mainly focusing on the study of soil structure (Mooney, 2002; Luo et al., 2010; Kravchenko et al., 2011), interactions between soil and microbes (Pajor et al., 2010; Crawford et al., 2011), and in vivo imaging of plant roots, root development, and architecture (Tracy et al., 2010, 2012). However, very few studies have applied X-ray CT to visualize and quantify the above-ground structures of plants, mainly because plant tissues have a low attenuation density, which results in low contrast and high levels of noise. A further
reason might be limited access to the highest resolution systems required to capture the cellular structure of plant tissues due to their recent introduction and high cost.
Using X-ray micro-CT to visualize and quantify Arabidopsis aerial tissues The first high-resolution micro-CT scans of plant tissues were restricted to synchrotron facilities. For example, Cloetens et al. (2006) investigated the structure and spatial distribution of intracellular voids in the seeds of Arabidopsis (Fig. 1). Seeds were scanned at a spatial resolution of 60 nm using holotomography. The technique differs from traditional X-ray CT with an increased distance between the sample and detector. This approach also involves averaging over several projections taken at different, known distances from the detector, which enhances the phase contrast and allows more precise detection of object density. Kaminuma et al. (2008) used a commercially available CT scanner to obtain datasets of Arabidopsis leaves at a coarser resolution of 21 µm/pixel (Fig. 2). The level of detail was sufficient for the development of a model characterizing the spatial distribution of trichomes. Kaminuma et al. (2008) also scanned Arabidopsis seeds at a spatial resolution of 1 µm to demonstrate the capabilities of the technique. However, due to the low density of plant tissue material, sample movement, and the polychromatic beam, the datasets contained high levels of noise. More recently, Dhondt et al. (2010) obtained excellent images of the shoot and the flower of Arabidopsis at a resolution of 13.8 µm (in vivo) and the hypocotyl at 0.8 µm voxel size (ex vivo). However, scanning at this cellular resolution required fixation of the sample, dehydration, and staining with iodine to enhance the contrast. These procedures can potentially lead to artefacts in the final images and increase the time required for sample preparation. The present state of the art of high resolution, X-ray microCT units are now well capable of capturing the external morphology, as well as non-invasively visualizing and quantifying the internal structure of plant organs. Importantly, it is no
Fig. 1. Arabidopsis seed and intracellular voids visualized at a resolution of 60 nm using holotomography: (A) longitudinal 2D crosssection; (B) 3D rendering of segmented hypocotyl voids. Bars, 50 µm. From: Quantitative phase tomography of Arabidopsis seeds reveals intercellular void network. Cloetens P, Mache R, Schlenker M, Lerbs-Mache S. 2006. Proceedings of the National Academy of Sciences, USA 103, 14626–14630. Copyright (2006) National Academy of Sciences, USA.
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Fig. 2. Quantifying locations of Arabidopsis leaf trichomes using X-ray micro-CT: (A) 3D false colouring render of Arabidopsis leaves scanned at spatial resolution of 21 µm; (B) leaf blade with trichome locations automatically detected by image analysis. From: Quantitative analysis of heterogeneous spatial distribution of Arabidopsis leaf trichomes using micro X-ray computed tomography. Kaminuma E, Yoshizumi T, Wada T, Matsui M, Toyoda T. 2008. The Plant Journal 56, 470–482. Copyright (2008) John Wiley and Sons, UK.
longer necessary to fix samples or carry out additional staining to enhance the contrast. The high resolution allows the acquisition of representative datasets at cellular resolutions of c.1 µm. However, choosing the appropriate resolution has a large impact on the size of the sample that can be imaged and the size of the data set acquired. For example, choosing a coarse resolution in order to characterize a larger sample volume (field of view) can impair image quality and limit the ability to visualize discrete cells, but finer resolutions increase scan and processing times and restrict the volume that can be imaged.
The main advantage of X-ray micro-CT is that it is closely bound with rapidly progressing image analysis. Advanced software packages now allow accurate quantification of the structural characteristics of the tissue that are inherently linked to cellular architecture, such as porosity, void/ pore size, connectivity, tortuosity, and surface area in 3D. Effectively, it is possible to obtain morphological descriptors of plant organs, then peel away the exterior structure of the sample and visualize/quantify the 3D complexity of the underlying porous architecture at cellular level (Fig. 3).
Fig. 3. 3D visualization of segmented intracellular pore space (yellow) from the tip of the Arabidopsis leaf (scanned at 4.5 µm with the GE|Phoenix Nanotom system) illustrated by peeling the plant tissue (green) away to reveal underlying cellular structure (NB: yellow refers to voids within cells rather than cell material). On top of the morphological descriptors of the leaves, from such segmented volume it is also possible to rapidly acquire parameters on relative cell/void structure and void size, shape, and distribution. Bar, 1.5 mm.
388 | Viewpoint The undisputed advantage of scanning aerial plant tissues as opposed to subterranean root tissues is that it is a relatively trivial imaging challenge to segment the solid components of leaf material from the surrounding air, compared to the much more difficult process of segmenting roots from the surrounding soil matrix due to its multiphase nature (e.g. Tracy et al., 2012). As noise within the data has a lesser effect on
surface determination in two phases compared to multiphase systems, scan times can be significantly reduced (to a few minutes), ensuring that large sample numbers and replicates can be easily accommodated within an experimental design (Fig. 4). This is important because short scan times are crucial if it comes to destructively sampling aerial plant tissues (i.e. plant discs) to avoid wilting of the material which affects the
Fig. 4. The trade-off between sample size and resolution. (A) Cross-sections through the thickest part of the Arabidopsis leaf, scanned at 15, 4.5, and 2.7 µm resolution (as indicated). (B) 3D visualization of the volumes which can be scanned at the two resolutions as indicated. Bar, 4.5 mm (B).
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Fig. 5. 3D visualization of an Arabidopsis seed pod scanned at a resolution of 12 µm (A) and an Arabidopsis inflorescence scanned at a resolution of 17 µm (B). Datasets were obtained using the GE|Phoenix Nanotom. Bars, 0.55 mm (B).
quality of data. It is also possible to characterize the internal structure of whole organs such as seed pods, leaves, or inflorescences in vivo (Fig. 5), allowing observation of structural development over time. The main current limitations to the technique at present are the previously mentioned resolution versus sample size trade off, reducing image noise, and the lengthy sample preparation required to get the best-quality images. Further work is needed to improve the scanning protocols to reduce movement of plant tissues during a scan in vivo, which is a challenge with complex and fragile structures. Once resolved, this may lead to automated, rapid screening of plant tissue development in 3D over time, possibly using new, high-throughput, glasshouse imaging platforms (Furbank and Tester, 2011) that utilize conveyor systems for delivering plants to imaging chambers. Such novel data are crucial for studies seeking to understand the impacts of cellular structural architecture on the physiological behaviour of plant tissues. For example, there is an extensive theoretical literature dealing with gas flux within leaves and how this represents a significant restriction on the overall efficiency of photosynthesis (Terashima et al., 2011). However the experimental data on air space distribution are
actually quite limited and are frequently drawn from the interpretation of 2D imaging processes. The acquisition of accurate 3D data on air space patterning and how it develops will provide an enhanced and more extensive data which can be used to test the accuracy of these models which is urgently needed. It will also allow improvement of these models and potentially permit identification of novel traits for selection to improve photosynthetic performance, a research area at the core of efforts to improve global food security. It will also provide data on the process of air space formation itself, a topic on which surprisingly little is known from a molecular aspect.
Summary X-ray micro-CT is a rapidly developing imaging technique allowing non-destructive visualization and quantification of the internal structures of plant organs at a resolution of c.1 µm in 3D. The technique allows the quantification of morphological and structural changes occurring in plant organs such as roots in vivo, over time. Although scanning of aerial
390 | Viewpoint plant organs in vivo still remains a time-consuming challenge, both the equipment and scanning procedures are progressing very quickly, improving the quality of data and broadening the potential areas of use. The introduction of 3D structural complexity to existing models of biochemical and physiological processes will lead to a deeper understanding of plant physiology, significantly expanding insight into the effect of the 3D leaf intracellular void network structure on CO2 flux and the effect this has on photosynthetic efficiency. Finally, observation of the development of 3D internal leaf structure over time will enable the monitoring of growth dynamics and differentiation, providing a crucial framework for the dissection of the molecular and cellular processes underpinning these events.
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