Investigating the microstructure of plant leaves in 3D with lab-based X-ray computed tomography

Mathers, Andrew and Hepworth, Christopher and Baillie, Alice L. and Sloan, Jen and Jones, Hannah and Lundgren, Marjorie Ruth and Fleming, Andrew J. and Mooney, Sacha J. and Sturrock, Craig J. (2018) Investigating the microstructure of plant leaves in 3D with lab-based X-ray computed tomography. Plant Methods, 14 (1). ISSN 1746-4811

PDF (Mathers_etal_PlantMethods_AcceptedVersion)
Mathers_etal_PlantMethods_AcceptedVersion.pdf - Accepted Version
Available under License Creative Commons Attribution.

Download (764kB)


Background: 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. Results: We used the microCT image pipeline to obtain estimates of leaf porosity and mesophyll exposed surface area (Smes) 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 Smes for the dicot species whereas barley had the highest porosity and the highest Smes for the grass species. Comparison of porosity and Smes 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 Smes by almost 50%. A deeper study of porosity revealed similarities and differences in the asymmetric distribution of airspace between the species analysed. Conclusions: 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 Smes 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. © 2018 The Author(s).

Item Type:
Journal Article
Journal or Publication Title:
Plant Methods
Additional Information:
Export Date: 6 December 2018 Correspondence Address: Sturrock, C.J.; University of Nottingham, Division of Agricultural and Environmental Sciences, School of Biosciences, Sutton Bonington Campus, United Kingdom; email: References: Ray, D.K., Mueller, N.D., West, P.C., Foley, J.A., Yield trends are insufficient to double global crop production by 2050 (2013) PLoS ONE, 8 (6); Long, S.P., Marshall-Colon, A., Zhu, X.-G., Meeting the global food demand of the future by engineering crop photosynthesis and yield potential (2015) Cell, 161 (1), pp. 56-66; Glowacka, K., Kromdijk, J., Kucera, K., Xie, J.Y., Cavanagh, A.P., Leonelli, L., Photosystem II Subunit S overexpression increases the efficiency of water use in a field-grown crop (2018) Nat Commun, 9, p. 868; Kromdijk, J., Glowacka, K., Leonelli, L., Gabilly, S.T., Iwai, M., Niyogi, K.K., Improving photosynthesis and crop productivity by accelerating recovery from photoprotection (2016) Science, 354 (6314), pp. 857-861; Long, B.M., Hee, W.Y., Sharwood, R.E., Rae, B.D., Kaines, S., Lim, Y.L., Carboxysome encapsulation of the CO2-fixing enzyme Rubisco in tobacco chloroplasts (2018) Nat Commun, 9, p. 3570; Mathan, J., Bhattacharya, J., Ranjan, A., Enhancing crop yield by optimizing plant developmental features (2016) Development (Cambridge, England), 143 (18), pp. 3283-3294; Evans, J.R., Kaldenhoff, R., Genty, B., Terashima, I., Resistances along the CO2 diffusion pathway inside leaves (2009) J Exp Bot, 60 (8), pp. 2235-2248; Park, S., Internal leaf area and cellular CO2 resistance: photosynthetic implications of variations with growth conditions and plant species (1977) Physiol Plant, 40, pp. 137-144; Turrell, F.M., The area of the internal exposed surface of dicotyledon leaves (1936) Am J Bot, 23 (4), pp. 255-264; Thain, J.F., Curvature correction factors in the measurement of cell surface areas in plant tissues (1983) J Exp Bot, 34 (138), pp. 87-94; James, S.A., Smith, W.K., Vogelmann, T.C., Ontogenetic differences in mesophyll structure and chlorophyll distribution in Eucalyptus globulus ssp. globulus (1999) Am J Bot, 86 (2), pp. 198-207; Theroux-Rancourt, G., Earles, J.M., Gilbert, M.E., Zwieniecki, M.A., Boyce, C.K., McElrone, A.J., The bias of a two-dimensional view: comparing two-dimensional and three-dimensional mesophyll surface area estimates using noninvasive imaging (2017) New Phytol, 215 (4), pp. 1609-1622; As, H., Scheenen, T., Vergeldt, F.J., MRI of intact plants (2009) Photosynth Res, 102 (2-3), pp. 213-222; Metzner, R., Eggert, A., Dusschoten, D., Pflugfelder, D., Gerth, S., Schurr, U., Direct comparison of MRI and X-ray CT technologies for 3D imaging of root systems in soil: potential and challenges for root trait quantification (2015) Plant Methods, 11, p. 17; Schmittgen, S., Metzner, R., Dusschoten, D., Jansen, M., Fiorani, F., Jahnke, S., Magnetic resonance imaging of sugar beet taproots in soil reveals growth reduction and morphological changes during foliar Cercospora beticola infestation (2015) J Exp Bot, 66 (18), pp. 5543-5553; Metzner, R., Dusschoten, D., Bühler, J., Schurr, U., Jahnke, S., Belowground plant development measured with magnetic resonance imaging (MRI): exploiting the potential for non-invasive trait quantification using sugar beet as a proxy (2014) Front Plant Sci, 5, p. 469; Li, K., Song, W., Zhu, L., Observation and measurement of plant root architecture in situ: a review (2011) Shengtaixue Zazhi, 30 (9), pp. 2066-2071; Eberhard, M., Hardy, R., Steffen, O.-J., Johannes, F., André, G., Thomas, N., A functional imaging study of germinating oilseed rape seed (2017) New Phytol, 216 (4), pp. 1181-1190; Garbout, A., Munkholm, L.J., Hansen, S.B., Petersen, B.M., Munk, O.L., Pajor, R., The use of PET/CT scanning technique for 3D visualization and quantification of real-time soil/plant interactions (2012) Plant Soil, 352 (1-2), pp. 113-127; Sharpe, J., Optical projection tomography (2004) Annu Rev Biomed Eng, 6, pp. 209-228; Lee, K., Avondo, J., Morrison, H., Blot, L., Stark, M., Sharpe, J., Visualizing plant development and gene expression in three dimensions using optical projection tomography (2006) Plant Cell, 18 (9), pp. 2145-2156; Flannery, B.P., Deckman, H.W., Roberge, W.G., D'Amico, K.L., Three-dimensional X-ray microtomography (1987) Science (New York, NY)., 237 (4821), pp. 1439-1444; Dhondt, S., Vanhaeren, H., Loo, D., Cnudde, V., Inzé, D., Plant structure visualization by high-resolution X-ray computed tomography (2010) Trends Plant Sci, 15 (8), pp. 419-422; Marone, F., Mokso, R., Modregger, P., Fife, J., Pinzer, B., Thuring, T., Present and future X-ray tomographic microscopy at TOMCAT (2011) 10th international conference on X-ray microscopy. AIP conference proceedings, 1365, pp. 116-119. , McNulty I, Eyberger C, Lai B, editors; Verboven, P., Kerckhofs, G., Mebatsion, H.K., Ho, Q.T., Temst, K., Wevers, M., Three-dimensional gas exchange pathways in pome fruit characterized by synchrotron X-ray computed tomography (2008) Plant Physiol, 147 (2), pp. 518-527; Kaminuma, E., Yoshizumi, T., Wada, T., Matsui, M., Toyoda, T., Quantitative analysis of heterogeneous spatial distribution of Arabidopsis leaf trichomes using micro X-ray computed tomography (2008) Plant J Cell Mol Biol, 56 (3), pp. 470-482; Schneider, J.V., Rabenstein, R., Wesenberg, J., Wesche, K., Zizka, G., Habersetzer, J., Improved non-destructive 2D and 3D X-ray imaging of leaf venation (2018) Plant Methods, 14, p. 7; Jhala, V.M., Thaker, V.S., X-ray computed tomography to study rice (Oryza sativa L.) panicle development (2015) J Exp Bot, 66 (21), pp. 6819-6825; Niet, T., Zollikofer, C.P., León, M.S., Johnson, S.D., Linder, H.P., Three-dimensional geometric morphometrics for studying floral shape variation (2010) Trends Plant Sci, 15 (8), pp. 423-426; Stuppy, W.H., Maisano, J.A., Colbert, M.W., Rudall, P.J., Rowe, T.B., Three-dimensional analysis of plant structure using high-resolution X-ray computed tomography (2003) Trends Plant Sci, 8 (1), pp. 2-6; Staedler, Y.M., Masson, D., Schoenenberger, J., Plant tissues in 3D via X-ray tomography: simple contrasting methods allow high resolution imaging (2013) PLoS ONE, 8 (9); Tracy, S.R., Gomez, J.F., Sturrock, C.J., Wilson, Z.A., Ferguson, A.C., Non-destructive determination of floral staging in cereals using X-ray micro computed tomography (microCT) (2017) Plant Methods, 13, p. 9; Herremans, E., Verboven, P., Verlinden, B.E., Cantre, D., Abera, M., Wevers, M., Automatic analysis of the 3-D microstructure of fruit parenchyma tissue using X-ray micro-CT explains differences in aeration (2015) BMC Plant Biol, 15, p. 264; Dorca-Fornell, C., Pajor, R., Lehmeier, C., Pérez-Bueno, M., Bauch, M., Sloan, J., Increased leaf mesophyll porosity following transient retinoblastoma-related protein silencing is revealed by microcomputed tomography imaging and leads to a system-level physiological response to the altered cell division pattern (2013) Plant J Cell Mol Biol, 76 (6), pp. 914-929; Lehmeier, C., Pajor, R., Lundgren, M.R., Mathers, A., Sloan, J., Bauch, M., Cell density and airspace patterning in the leaf can be manipulated to increase leaf photosynthetic capacity (2017) Plant J Cell Mol Biol, 92 (6), pp. 981-994; Schneider, C.A., Rasband, W.S., Eliceiri, K.W., NIH Image to ImageJ: 25years of image analysis (2012) Nat Methods, 9 (7), pp. 671-675; Doube, M., Klosowski, M.M., Arganda-Carreras, I., Cordelieres, F.P., Dougherty, R.P., Jackson, J.S., BoneJ Free and extensible bone image analysis in ImageJ (2010) Bone, 47 (6), pp. 1076-1079; Schindelin, J., Arganda-Carreras, I., Frise, E., Kaynig, V., Longair, M., Pietzsch, T., Fiji: an open-source platform for biological-image analysis (2012) Nat Methods, 9 (7), pp. 676-682; Giuliani, R., Koteyeva, N., Voznesenskaya, E., Evans, M.A., Cousins, A.B., Edwards, G.E., Coordination of leaf photosynthesis, transpiration, and structural traits in rice and wild relatives (genus Oryza) (2013) Plant Physiol, 162 (3), pp. 1632-1651; Legland, D., Devaux, M.-F., Guillon, F., Quantitative imaging of plants: multi-scale data for better plant anatomy (2018) J Exp Bot, 69 (3), pp. 343-347; Karunakaran, C., Lahlali, R., Zhu, N., Webb, A.M., Schmidt, M., Fransishyn, K., Factors influencing real time internal structural visualization and dynamic process monitoring in plants using synchrotron-based phase contrast X-ray imaging (2015) Sci Rep, 5, p. 12119; Keyes, S.D., Daly, K.R., Gostling, N.J., Jones, D.L., Talboys, P., Pinzer, B.R., High resolution synchrotron imaging of wheat root hairs growing in soil and image based modelling of phosphate uptake (2013) New Phytol, 198 (4), pp. 1023-1029; Koebernick, N., Daly, K.R., Keyes, S.D., George, T.S., Brown, L.K., Raffan, A., High-resolution synchrotron imaging shows that root hairs influence rhizosphere soil structure formation (2017) New Phytol, 216 (1), pp. 124-135; Hopkins, T.M., Heilman, A.M., Liggett, J.A., LaSance, K., Little, K.J., Hom, D.B., Combining micro-computed tomography with histology to analyze biomedical implants for peripheral nerve repair (2015) J Neurosci Methods, 255, pp. 122-130; Girard, R., Zeineddine, H.A., Orsbon, C., Tan, H., Moore, T., Hobson, N., Micro-computed tomography in murine models of cerebral cavernous malformations as a paradigm for brain disease (2016) J Neurosci Methods, 271, pp. 14-24
Uncontrolled Keywords:
ID Code:
Deposited By:
Deposited On:
05 Nov 2018 10:16
Last Modified:
27 Sep 2020 04:55