The influences of stomatal size and density on rice abiotic stress resilience.

A warming climate coupled with reductions in water availability and rising salinity are increasingly affecting rice (Oryza sativa) yields. Elevated temperatures combined with vapour pressure deficit (VPD) rises are causing stomatal closure, further reducing plant productivity and cooling. It is unclear what stomatal size (SS) and stomatal density (SD) will best suit all these environmental extremes. To understand how stomatal differences contribute to rice abiotic stress resilience, we screened the stomatal characteristics of 72 traditionally bred varieties. We found significant variation in SS, SD and calculated anatomical maximal stomatal conductance (gsmax ) but did not identify any varieties with SD and gsmax as low as transgenic OsEPF1oe plants. Traditionally bred varieties with high SD and small SS (resulting in higher gsmax ) typically had lower biomasses, and these plants were more resilient to drought than low SD and large SS plants, which were physically larger. None of the varieties assessed were as resilient to drought or salinity as low SD OsEPF1oe transgenic plants. High SD and small SS rice displayed faster stomatal closure during increasing temperature and VPD, but photosynthesis and plant cooling were reduced. Compromises will be required when choosing rice SS and SD to tackle multiple future environmental stresses.

Defining the scope for altering rice leaf anatomy to improve photosynthesis: a modelling approach.

Leaf structure plays an important role in photosynthesis. However, the causal relationship and the quantitative importance of any single structural parameter to the overall photosynthetic performance of a leaf remains open to debate. In this paper, we report on a mechanistic model, eLeaf, which successfully captures rice leaf photosynthetic performance under varying environmental conditions of light and CO2 . We developed a 3D reaction-diffusion model for leaf photosynthesis parameterised using a range of imaging data and biochemical measurements from plants grown under ambient and elevated CO2 and then interrogated the model to quantify the importance of these elements. The model successfully captured leaf-level photosynthetic performance in rice. Photosynthetic metabolism underpinned the majority of the increased carbon assimilation rate observed under elevated CO2 levels, with a range of structural elements making positive and negative contributions. Mesophyll porosity could be varied without any major outcome on photosynthetic performance, providing a theoretical underpinning for experimental data. eLeaf allows quantitative analysis of the influence of morphological and biochemical properties on leaf photosynthesis. The analysis highlights a degree of leaf structural plasticity with respect to photosynthesis of significance in the context of attempts to improve crop photosynthesis.

Estimating uncertainty: A Bayesian approach to modelling photosynthesis in C3 leaves.

The Farquhar-von Caemmerer-Berry (FvCB) model is extensively used to model photosynthesis from gas exchange measurements. Since its publication, many methods have been developed to measure, or more accurately estimate, parameters of this model. Here, we have created a tool that uses Bayesian statistics to fit photosynthetic parameters using concurrent gas exchange and chlorophyll fluorescence measurements whilst evaluating the reliability of the parameter estimation. We have tested this tool on synthetic data and experimental data from rice leaves. Our results indicate that reliable parameter estimation can be achieved whilst only keeping one parameter, Km , that is, Michaelis constant for CO2 by Rubisco, prefixed. Additionally, we show that including detailed low CO2 measurements at low light levels increases reliability and suggests this as a new standard measurement protocol. By providing an estimated distribution of parameter values, the tool can be used to evaluate the quality of data from gas exchange and chlorophyll fluorescence measurement protocols. Compared to earlier model fitting methods, the use of a Bayesian statistics-based tool minimizes human interaction during fitting, reducing the subjectivity which is essential to most existing tools. A user friendly, interactive Bayesian tool script is provided.

Cell density and airspace patterning in the leaf can be manipulated to increase leaf photosynthetic capacity.

The pattern of cell division, growth and separation during leaf development determines the pattern and volume of airspace in a leaf. The resulting balance of cellular material and airspace is expected to significantly influence the primary function of the leaf, photosynthesis, and yet the manner and degree to which cell division patterns affect airspace networks and photosynthesis remains largely unexplored. In this paper we investigate the relationship of cell size and patterning, airspace and photosynthesis by promoting and repressing the expression of cell cycle genes in the leaf mesophyll. Using microCT imaging to quantify leaf cellular architecture and fluorescence/gas exchange analysis to measure leaf function, we show that increased cell density in the mesophyll of Arabidopsis can be used to increase leaf photosynthetic capacity. Our analysis suggests that this occurs both by increasing tissue density (decreasing the relative volume of airspace) and by altering the pattern of airspace distribution within the leaf. Our results indicate that cell division patterns influence the photosynthetic performance of a leaf, and that it is possible to engineer improved photosynthesis via this approach.

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.

The causal relationship between cell division and growth in plants is complex. Although altered expression of cell-cycle genes frequently leads to altered organ growth, there are many examples where manipulation of the division machinery leads to a limited outcome at the level of organ form, despite changes in constituent cell size. One possibility, which has been under-explored, is that altered division patterns resulting from manipulation of cell-cycle gene expression alter the physiology of the organ, and that this has an effect on growth. We performed a series of experiments on retinoblastoma-related protein (RBR), a well characterized regulator of the cell cycle, to investigate the outcome of altered cell division on leaf physiology. Our approach involved combination of high-resolution microCT imaging and physiological analysis with a transient gene induction system, providing a powerful approach for the study of developmental physiology. Our investigation identifies a new role for RBR in mesophyll differentiation that affects tissue porosity and the distribution of air space within the leaf. The data demonstrate the importance of RBR in early leaf development and the extent to which physiology adapts to modified cellular architecture resulting from altered cell-cycle gene expression.

Signalling between the sexes during pollen tube reception.

Plant reproduction is a complex, highly-coordinated process in which a single, male germ cell grows through the maternal reproductive tissues to reach and fertilise the egg cell. Focussing on Arabidopsis thaliana, we review signalling between male and female partners which is important throughout the pollen tube journey, especially during pollen tube reception at the ovule. Numerous receptor kinases and their coreceptors are implicated in signal perception in both the pollen tube and synergid cells at the ovule entrance, and several specific peptide and carbohydrate ligands for these receptors have recently been identified. Clarifying the interplay between these signals and the downstream responses they instigate presents a challenge for future research and may help to illuminate broader principles of plant cell-cell communication.

Conserved cellular patterning in the mesophyll of rice leaves.

The mesophyll cells of grass leaves, such as rice, are traditionally viewed as displaying a relatively uniform pattern, in contrast to the clear distinctions of palisade and spongy layers in typical eudicot leaves. This quantitative analysis of mesophyll cell size and shape in rice leaves reveals that there is an inherent pattern in which cells in the middle layer of the mesophyll are larger and less circular and have a distinct orientation of their long axis compared to mesophyll cells in other layers. Moreover, this pattern was observed in a range of rice cultivars and species. The significance of this pattern with relation to potential photosynthetic function and the implication of the widespread use of middle layer mesophyll cells as typical of the rice leaf have been investigated and discussed.

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

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.