Exploration of Optical Topometry to Study the Epidermal Surface of Arabidopsis thaliana Distinction Paper for Molecular and Cellular Biology Ryan David Kelsch Senior, Molecular and Cellular Biology University of Illinois at Urbana-­‐Champaign Research Advisor: Dr. Thomas Jacobs Ph.D Department of Plant Biology University of Illinois at Urbana-­‐Champaign March 27, 2013 Abstract The development of the epidermal surface in Arabidopsis thaliana is affected directly by environmental factors including those associated with climate change. Current methods for studying the surfaces of plants are tedious with evolving technology. Researchers studying epidermal development in plants are concerned with several functionally and structurally different cell types, whose development are governed by both environmental and genetic factors. A high throughput method to study the epidermal surface of plants that provides precise quantitative measurements for quantitative genetic analysis is therefore necessary. Optical topometry (OT, a subset of optical profilometry) is a technology used to map a micro-­‐scale surface in three dimensions and at nanometer precision. Such data sets can be mined by specialized software to perform analyses which can reveal biologically relevant features of a plant’s epidermal topography mediated by the three-­‐dimensional patterning of cells. My research used OT to reinvent known parameters and to discover novel parameters to describe the epidermal surface. In addition, wild type plants were compared to a reported epidermal cell mutant. Also in addition, developmental studies compared tissues within a single plant and also between plants at different developmental stages. Through these experiments, I was able to evaluate new parameters such as three-­‐dimensional surface area, which gives a quantitative snapshot of the overall topography. Established parameters were also measured, such as the tallying of key epidermal cells, as this is key to quantifying plant developmental responses to climate change. OT was able to obtain conclusive results in a high-­‐throughput fashion with no tissue preparation time and yielded three-­‐dimensional data sets indicative of the topographical features of the epidermis at the nanometer scale. This research has served as a proof-­‐of-­‐principle for creating a new standard for plant epidermal methodologies using optical topography, and has also opened doors for using optical topography to study any biological surface. Introduction Current methods for studying the epidermal surface of Arabidopsis thaliana (a model organism of plant biology) are tedious, especially in the face of evolving technology. Researchers in plant biology are concerned with the numbers of both pavement cells and stomata per unit area of the epidermis. Stomata are pairs of cells that are pair-­‐of-­‐lips like in morphology and are involved in gas exchange (CO2 in and H2O out). Pavement cells form a jigsaw puzzle-­‐like pattern over the majority of the epidermal surface area. The numbers from counting of these two cell types can be used to determine stomatal densities (the number of stomata per given area) and stomatal indices (Equation 1), which are established quantitative representations used for phenotyping and understanding underlying genetics. (Royer 2000). These phenotypes are of developmental interest due to our atmosphere’s increasing CO2 concentration and the stomate’s key role in removing CO2 from the atmosphere (IPCC, 2007). A high throughput method to study the epidermal surface of plants that provides the precise quantitative measurements needed for genetics would be of great service to the plant research community. 𝑆𝐼 % =
𝑠𝑡𝑜𝑚𝑎𝑡𝑎𝑙 𝑑𝑒𝑛𝑠𝑖𝑡𝑦
𝑋100 𝑠𝑡𝑜𝑚𝑎𝑡𝑎𝑙 𝑑𝑒𝑛𝑠𝑖𝑡𝑦 − 𝑒𝑝𝑖𝑑𝑒𝑟𝑚𝑎𝑙 𝑐𝑒𝑙𝑙 𝑑𝑒𝑛𝑠𝑖𝑡𝑦
Equation 1. Stomatal Index Equation The current method for generating images suitable for taking a census of cells populating the plant epidermis is via nail polish impressions. These are viewed under the microscope and cell counts are taken from recorded images. Image quality from nail polish impressions is variable to such a degree that automated counting via computer learning has not been possible. A more robust, higher throughput method could permit faster counting and the possibility of employing quantitative genetics and other numerically intensive methods to this all-­‐important interface between plants and the aerial environment. Optical topometry (OT) is a technology used to collect a set of images, layered in such a way to create a set of three-­‐dimensional data points that together describe the topographical features of a surface at potentially nanometer-­‐level precision. This mature technology finds intensive application in microelectronics and materials science, but has yet to be applied in a systematic fashion to many biological questions, particularly regarding plant surfaces. Data sets can be mined by dedicated software to generate an array of analyses that can be performed on a surface in three dimensions. A nail polish impression image, by contrast, tends to have low resolution of cells and high variability of quality, presenting a data set limited to the shading of pixels. OT generates functional data sets that can be manipulated and analyzed to an extent limited only by the investigator’s exploitation of existing, highly capable topographic analysis software (Figure 1). Other advantages of OT over nail polish include dramatically decreased sample preparation time (hours to seconds), the ability to take data directly on live tissue in a repeated non-­‐destructive fashion, and decreased variability between data sets so that automated counting is feasible. A B Figure 1. Optical Topometry and Nail Polish Comparison. Both images have the same unit area of the same leaf. OT rendering depicts surface slopes and Z-­‐
dimensional lobing, whereas this is absent from the largely 2D nail polish impression A. Rendering of intensity layer of OT data set. B. Nail polish impression image. In this study, the instrument used to obtain data sets describing the epidermal surface of A. thaliana was the NanoFocus μsurf Explorer. This instrument uses spinning disc confocal microscopy to obtain topometry data sets. While capturing the three-­‐dimensional data, the instrument also records an intensity rendering of the surface based on surface reflectivity (Figure 1A). Optical topometry offers a novel alternative to measuring important plant phenotypes. Other methods, such as scanning electron microcopy, atomic force microscopy (Mechaber, et al., 1996), dental resin impressions and nail polish impressions, are either too costly or destructive to the epidermal surface (due to preparation time or in the preparation used). Topographical techniques other than OT are time consuming, inaccurate and sometimes alter the tissue in their sample preparation (i.e. histological sectioning, other types of three-­‐dimensional microscopy) (Wutys, et al., 2010) (Truernit, et al., 2008). OT provides a solution that is inexpensive (apart from the initial cost of the instrument and software) and completely non-­‐destructive to the epidermal surface. It may also provide novel, measurable parameters that can be attained in a high throughput fashion. In order to explore this technology, three studies were undertaken, each intended to evaluate facets of OT as a viable approach to analyzing the epidermal surface of plants. Studies on Rop2 Mutants rop2 mutants of Arabidopsis thaliana display a decrease in interdigitation (lobing) of leaf epidermal pavement cells (Fu, et al., 2005). A lobe is defined an outgrowth from the cell center of a pavement cell, in the plane of a captured image (Fu, et al., 2005). In the context of three-­‐dimensional data sets, a lobe must be redefined as an area of local maximum in the z dimension, perpendicular to the plane of the leaf. This new definition also includes lobes of the cell center “backbone” area, since local maxima can be observed there using OT, but not via conventional microscopy as previously published (Fu, et al., 2005; Figure 2). rop2 acts in a pathway of microfilament formation that controls localized cell outgrowth (Fu, et al., 2005). Epidermal cell outgrowth also occurs in the z-­‐dimension (height), as seen in coordinate slices (surface profile along a particular line traced on the epidermal surface) of epidermal surfaces obtained by OT (Figure 2). A comparison is made in this study between Col-­‐0 (wt) and the rop 2 mutant as a proof of concept (in such parameters as lobing) and to investigate new parameters (such as overall surface area, lobing and lobe heights). Figure 2. Coordinate slice of A. thaliana epidermal surface. A. Surface filtered to remove 12 forms (removes any gradual trends), coordinates are marked on a topometry diagram of where a slice is to be made. B. Coordinate slice of line indicated in A, shows the varying heights along the “backbone” of the pavement cell centered in the red box. The brackets indicate regions of local maxima that translate into lobes in figure C. C. Resultant motif image of lobing pattern. The red box encompasses the same physical location for the three images. D. Intensity image containing the pavement cell of interest in the red box. Studies Across an Entire Plant Given that no published studies could be found that documented the development of leaf cellular microtopography throughout the life of a plant, I examined the entire leaf complement of several plants in an effort to identify trends from young to old leaves and within a single leaf. As younger leaves tend to have smaller pavement cells (Staff et al. 2012), it can be expected that leaves that are still developing would have a greater three-­‐dimensional surface area (due to a greater number of cell-­‐cell interfaces) and greater numbers of pavement cells per unit of two-­‐dimensional leaf area. With that in mind, parameters such as surface area, lobe and pavement number, and isotropy were chosen to determine if trends could be seen developmentally. Studies on Leaf Six Developmentally Leaf six of the wild type was chosen to look at developmentally, as it reaches full maturity within a reasonable time and has enough surface to take multiple measurements. The aim of this study was to determine if the three-­‐dimensional surface morphology of pavement cells -­‐-­‐ and that of the overall epidermal surface they create -­‐-­‐ change as a leaf and the plant matures. It was predicted that an overall decrease in pavement cells per two-­‐dimensional area would be observed as leaves matured, as younger leafs were seen in previous experiments (nail polish and SEM), to have more, smaller pavement cells than more senior leaves (Staff et al. 2012). It has also been shown that as pavement cells increase in size, interdigitation in the plane of the leaf (lobing) also increases (Staff et al. 2012). Number of lobes out of the plane of the leaf is predicted to also correlate to pavement cell size and number of pavement cells given the same two-­‐dimensional surface area. Materials and Methods Plant Growth Seeds were imbibed and stratified in deionized (DI) water at 4˚C for 3-­‐7 days before planting. Seeds were planted in in 4 x 9 cell Compak™ trays in autoclaved soil and vermiculite (LC1 Sunshine Professional growing mix and Strong-­‐lite ® medium vermiculite premium grade respectively), in a 3:1 ratio. For every 4L of soil mix, 2L of water with 2 g of Gnatrol WDG ® was added to the planting mixture. The plants were covered with a plastic dome until they reached approximately 10 mm in diameter. Plants were thinned to one plant per cell of the tray and watered with approximately 1 L of water per tray every week and after they reached about 20 mm, 0.5 grams of Gnatrol WDG ® and 0.75 g of Peter’s Fertilizer was added to the weekly 1 L watering mixture. After approximately 1-­‐2 months (Table 1, growth time depends on particular experiment) of growth in 12 hr days (fluorescent light) at 20-­‐
22° C, measurements were taken with OT and then nail polish impressions were taken and catalogued (Table 1). Accession/Mutant Number of Plants Viewed Days of Growth Leaf Before Viewing (Leaves) Experiment Viewed Rop2 2 27 1 Studies on Rop2 Mutants Col0 3 49 6 Studies on Leaf Six Developmentally Col0 3 43 6 Studies on Leaf Six Developmentally Col0 3 32 6 Studies on Leaf Six Developmentally Col0 5 27 (leaf 1) 28 (leaf 1 and 6 Studies on Rop2 Mutants and Studies on 6) Leaf Six Developmentally Col0 1 63-­‐65 1 thru 40 Studies Across an Entire Plant Col0 1 71-­‐72 1 thru 42 Studies Across an Entire Plant Col0 1 79-­‐80 3 thru 50 Studies Across an Entire Plant Table 1. Growth time before data collection. Viewing refers to OT data collection and then impression taking. Data Collection Data were collected for each of the studies using the NanoFocus μsurf Explorer and via conventional nail polish impressions (using nail polish on the abaxial surface, and then removal with tape). The abaxial surface of each leaf was affixed to a glass microscope slide with double-­‐sided tape. Data were collected within 3 minutes after each leaf was removed from the plant. All data were collected using the instrument’s 50x objective focused at a point midway between veins. For the studies on rop2 mutants, data were taken at three points, proximal medial and distal to the point of attachment of the leaf to the plant, on both sides of the central vein. For the studies across an entire plant, data were taken between each vein, between the tip and the distal-­‐most vein and between the base and the basal-­‐most vein. For the leaf six developmental studies, data were taken at a medial position, on both sides of the central vein. Every data set was measured with the same two-­‐
dimensional area. Data Processing All data processing was performed using Nanofocus’s proprietary μsoft Analysis Premium software package. This software tool includes a wide variety of surface analysis algorithms of both industry-­‐specific and more general purpose natures. The software provides a variety of filters as well as offering the user the option to make fine adjustments away from the system’s defaults. In order to enable the software to identify individual pavement cells, cell-­‐to-­‐cell boundaries had to be exaggerated. Twelve forms of the topometry surface were removed, eliminating the gradual variation in height across the surface. For cell identification and counting, a spatial filter was then applied that takes advantage of the height minima that occur at cell-­‐to-­‐cell interfaces. The filter negatively amplified all minima below a manually-­‐set threshold, while the points directly adjacent to the minima were positively amplifed to maxima (this is a so-­‐called Mexican Hat filter). All points that were not considered a minimum were then flattened so that the end result was flattened pavement cell bodies surrounded by elevated cell wall interfaces surrounding deep valleys between cells (Figure 3). A motif analysis was then performed to detect pavement cells. Pavement cells were detected by asking the program to search for local minima motifs that are at least 6% of the highest maxima (to occlude the valleys between cells), and were at least 1% of the overall surface area (to occlude stomata, other cell types, and artifacts) (Figure 4). Although automated counting compared to manual counting does not always produce the same results (automated counting tends to cut up larger pavement cells into several motifs), automated means of counting remove any bias. If the identical counting procedures are used to obtain all data sets, then differences should be noted, regardless of differences between manual and automated counting in methods for counting pavement cells. Figure 3. Three-­‐dimensional rendering of spatially filtered surface. Light orange indicates a pavement cell body, dark orange the exaggerated maxima, and yellow the exaggerated minima. Figure 4. Motif analysis for pavement cell detection. Different colored segments are computer counted pavement cells. Crosses are placed on minima of a motif. Colors are overlaid on original 12-­‐forms removed image. Lobing requires the surface to be somewhat unaltered by the software to obtain an accurate count of the number of lobes per unit area so that local maxima are preserved. As in the case of searching for pavement cells, twelve forms were removed from the surface. Defining a lobe as a local maximum in height (Figure 2), a motif analysis was performed based on local maximal heights such that each motif must be less than 0.1% of the overall surface area, the approximate size of a pavement cell lobe (Figure 2C). The heights of these local maxima lobe motifs were also recorded and averaged to produce an average lobe height. Finally, μsoft Analysis Premium can calculate the three-­‐dimensional surface area of a surface in a given frame of view. It also can measure the overall isotropy of a surface (directional independence, given as a percentage) and the first, second, and third directions (prevailing orientation of objects) for any data set. Statistical Analysis For the studies on rop2 mutants, a t-­‐test was used with a least similar differences function with an alpha of 0.05. For the studies across an entire plant, an ANOVA was used with covariance matrices because the data points were spatially related. Each dependent variable covariance matrix was independently analyzed. For the studies on leaf six developmentally, a t-­‐test was used with a least similar differences function with an alpha of 0.05 and a nested design. Results Studies on Rop2 Mutants Optical topometry data sets for rop2 mutants (SALK line t-­‐DNA insertion, SALK_055328C) and Col-­‐0 (wildtype) epidermis were collected from the first matured leaf, on both sides of the central vein, and between bisecting veins proximally, medially, and distally from the stem to the tip. The topometry portion of each data set was analyzed using μSurf Analysis parameters. Lobe parameters were determined from local maxima of the z-­‐dimension (e.g. height), as well as a maximum area of 0.1% of the surface area restriction. Motif analysis of lobe number suggests a decrease in rop2 compared to Col-­‐0, with decreased average height of lobe motifs for the rop2 mutant (Figure 5BC). Motif analysis parameters of total pavement cell numbers, after flattening of the surface and exaggerating cell-­‐to-­‐cell interfaces, indicate no difference between Col-­‐0 and rop2 (Figure 5A). Surface area of the epidermis also displays an overall increase for the wt compared to rop2 (Figure 5D). Figure 5. rop2 vs. wt epidermis. Analyses were performed on the entire data set of a given area of the plant surface. A. Cell numbers were determined per unit area after flattening and filtering the surface based on depression motifs that were at least 6% of the highest peak and at least 1% of the overall surface area (p=0.4895). B. Number of lobes per unit area were counted using height motifs generated using an area of less than 0.1% of the total surface area (p=0.0285). C. Average lobe height per unit area was measured from the center maxima of the lobe motif (p=0.0049) D. Three dimensional surface area was measured across the unit area for each data set (p=0.007). Studies Across an Entire Plant Optical topometry data sets were obtained of the epidermal surface of three plants on every leaf that had not yet senesced, in every position between bisecting veins, before the most proximal bisecting vein and after the last distal bisecting vein, left of the central vein only. Variable Parameter Leaf Placement Leaf*Placement Pavement Cells 0.0001 0.0048 0.7041 Lobes 0.001 0.002 0.889 Lobe Height 0.3327 0.1034 0.9987 Surface Area 0.0001 0.0001 0.9873 Isotropy 0.41 0.7424 0.9732 First Direction 0.3135 0.2651 0.2715 Second Direction 0.3135 0.2651 0.3715 Third Direction 0.6742 0.0649 0.6649 Table 2. P values for studies across an entire plant. Isotropy and its first, second and third directions were statistically insignificant (Table 2), but their respective histograms show interesting groupings at certain directions. It can be seen at the approximately 0°, 45°, 90°, and 135° directions (Figure 6), that there are large groupings in the first, second and third directions. In addition, isotropy has lower values, which indicates some directionality in the features of the surface. B A C D Figure 6. Isotropy and directions for entire plant. A. Histogram of isotropy, the x-­‐
axis is percentage. B. Histogram of first direction, the x-­‐axis is degrees (0-­‐180°). C. Histogram of second direction, the x-­‐axis is degrees (0-­‐180°). D. Histogram of third direction, the x-­‐axis is degrees (0-­‐180°). Surface area, lobe number and pavement cell number are all significant in placement across a leaf (proximal to distal) and from leaf to leaf (Table 2). Lobe height, while not significant at leaf or placement, is also grouped with these parameters since its data follows a similar trend. 3D surface area, lobe height, lobe number, and pavement cell number all follow the trend of having higher values in young and old leaves and intermediate values in the leaves that are aged between, creating an inverse bell curve (Figure 7). Lobe number and pavement cell number follow the same trend across placement (proximal to distal), having inverse bell curve shaped graphs, whereas 3D surface area and lobe height both have standard bell curve shaped graphs. Figure 7. 3D surface area, lobe height, lobe number, and pavement cell number across leaves and placement of entire plants. Placement 1-­‐7 on the x-­‐
axis is proximal to distal. Placement number 7 had only one value and is considered an outlier. Leaves are numbered 1-­‐50 from oldest to youngest leaves. A. 3D surface area across leaves (in µm²E2). B. 3D surface area across placement (in µm²E2). C. Lobe height across leaves (µm E-­‐2). D. Lobe height across placement (µm E-­‐2). E. Lobe number across leaves. F. Lobe number across placement. G. Pavement cell number across leaves. H. Pavement cell number across placement. Studies on Leaf Six Developmentally Optical topography data sets were taken bilaterally of the central vein on wt Col-­‐0 plants at a position midway between the central vein and the leaf margin. The same filtering and parameterization that was used for the studies on rop2 mutants was applied. Results showed values that were mostly insignificantly different across development. The total pavement cell number varies insignificantly from week to week (Figure 8A), whereas lobing, lobe height, and 3D surface area show significant differences between weeks 5 and 6 of development (Figure 8BCD). Figure 8. wt epidermis developmentally. Analyses were performed on the entire data set of a given area of the plant surface. A. Number of cells were counted per unit area after flattening and filtering the surface based on depression motifs that were at least 6% of the highest peak and at least 1% of the overall surface area (p=0.246). B. Number of lobes per unit area were counted using height motifs generated using an area of less than 0.1% of the total surface area (p=0.0006). C. Average lobe height per unit area was measured from the center maxima of the lobe motif (p=0.008) D. Three-­‐dimensional surface area was measured across the unit area of data taken for each data set taken (p=0.0013). Discussion and Conclusion Studies on Rop2 Mutants From the mutant studies of rop2, a picture begins to emerge of the morphological differences between the mutant and wildtype. Since the overall pavement cell number remains constant between the mutant and the wildtype per unit area, it can be said that although there are some obvious changes in lobe number, lobe height and overall surface area, the average 2D area that a given pavement cell occupies must remain relatively constant. This is not true of the 3D area. With an increase in 3D surface area, lobe number, and lobe heights, it can be said that the wildtype is in generally more “lumpy” than the mutant, with more incidents of height maxima, generating more lobe motifs and a greater overall surface area. This is not to say the level of interdigitation in rop2 is less than the wildtype, but that lobing is less exaggerated in the mutant so much that local maxima begin to disappear. These results are not surprising in that it has been shown that rop2 carries a defect in microtubule and microfilament arrangements that impact pavement cell morphologies, and mutants were reported to display a decrease in lobing in two-­‐dimensions (Fu, et al., 2005). Studies Across an Entire Plant In looking at the entire A. thaliana leaf epidermis, several trends were apparent. Isotropically, having the directions of 0°, 45°, 90°, and 135°, showing a strong bias (Figure 8) indicates some directionality in the surface. Since the leaf was viewed in the same position with the central vein always oriented in a north-­‐south fashion, these angles show some disposition to the orientation of cells at an angle with or in line with the central vein. The angled dispositions may be a result of the radiating veins that branch from the central vein at approximately 45°. Analyzing 3D surface area, lobe height, lobe number, and pavement cell number, the similar inverse bell curve trend can be seen in all cases, from old to new leaves. Old and young leaves tend to be smaller and contain more compact pavement cells, giving rise to a greater 3D surface area due to a greater number of cell-­‐cell valleys and greater number of pavement cells and number of lobes (in this case the number of pavement cells outweighs the increase in lobing that is seen with greater size of pavement cells). The increase in height seen may be a result from the overall compactness of the pavement cells, having not yet fully expanded. For placement within a leaf, across all leaves, the most distal and proximal regions have greater numbers of pavement cells and more lobing, but a decrease in 3D surface area and lobe height. In this case, the larger pavement cells of the more central regions of the leaf have a greater height than those at the periphery, exaggerating the cell-­‐cell valleys and local undulations, taking up a greater surface area. These two opposing trends can be seen in Figure 9. The overall inverse bell curve can be seen across the entire graph for 3D surface area, illustrating pavement cell number outweighing the factors from large pavement cells. The local undulations in the curve indicate a movement from proximal to distal locations within a leaf, showing the large pavement cell factors outweighing the small pavement cell factors. 3D SA (µm²E2) 1250 1200 1150 1100 1050 950 900 1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 104 110 116 122 128 134 140 146 152 158 164 170 176 182 188 194 200 206 212 218 224 1000 leaf*placement Figure 9. 3D Surface Area leaf*placement graph. The x-­‐axis numbers indicate both leaf and placement in an increasing fashion from both proximal to distal and both old to new leaf (ex. numbers 1-­‐3 indicate the proximal to distal positions on leaf 1, the numbers 4-­‐6 indicate the proximal to distal positions on leaf 2…the numbers 11-­‐15 indicate the proximal to distal positions on leaf 4, etc.)
Studies on Leaf Six Developmentally Departures from results predicted for the developmental survey are most likely due to specimen maturities being overly biased in the direction of too mature to detect significant differences in pavement cell number. The relative decrease in lobing and surface area are positively correlated. This observation is readily rationalized, since lobing measurements are based on local height maxima, the less “bumpy” the surface is, the lower the measured surface area is expected to be. In addition, the height decrease observed between weeks five and six correlates positively with a decrease in lobe number. It can be extrapolated that late in development (between weeks five and six), leaf six undergoes a physiological-­‐
morphological transition that flattens, but does not expand its pavement cells. This flattening may be attributed to the removal of water to other still developing parts of the plant, resulting in a decrease in turgor pressure from the water vacuole. This also could be explained by the increase in cellulose in the cell wall of as pavement cells develop, increasing their ability to resist turgor pressure expansion. Implications for Future Research Optical topometry is a high throughput tool that shows terrific promise for enabling large scale sampling of plant epidermal surfaces. For taking cell censuses, pavement cells can be identified and counted from Arabidopsis and undoubtedly most other species, Arabidopsis being especially challenging with its highly irregular, jigsaw puzzle epidermis. We have made progress in applying OT to identifying stomata, but more work, and possibly purpose-­‐written software, is needed for this to become as reliable as it is for pavement cells. By creating a binary image from the original Arabidopsis pavement cell filtering protocol, stomata can be identified by the naked eye. Machine counting is therefore at least theoretically within reach, although more work needs to be done to optimize it (Figure 10). With automated counting of both stomata and pavement cells in hand, stomatal indices and densities can be determined essentially instantaneously, massively accelerating the quantitative, cellular phenotyping of plant epidermises for large scale genetic studies. In addition to greatly facilitating cell census taking, OT opens up barely-­‐
explored opportunities for characterizing novel surface features with high precision. For example, lobe analysis has never before been performed on a plant epidermis in the z-­‐dimension and represents a phenotype ripe for genetic analysis. In addition, three-­‐dimensional surface area is a novel parameter with potentially valuable implications for modeling the plant-­‐air interface. Finally, all measurements derived from OT can be logged in high-­‐throughput fashion, enabling large scale explorations of these heretofore cryptic plant phenotypes. * Figure 10. Binary image of epidermal surface. Pavement cells are colored and cell-­‐cell boundaries are in light yellow. The binary nature is cell body and cell wall. *Indicates a stomata that can clearly be seen and possibly isolated automatically in the future. Acknowledgements I would like to thank Dr. Tom Jacobs and Miranda Haus for all of their help along the way of this project in guiding my research. Miranda Haus ran all of the statistics. I would also like to thank Chris Wichern (Nanofocus, USA) for providing the µSurf Explorer instrument, the µSoft Analysis Premium software and training in the use of both the hardware and software. References Fu, Y., Gu, Y. Zheng, Z., Wasteneys, G., Yang, Z. (2005). Arabidopsis Interdigitating Cell Growth Requires Two Antagonistic Pathways with Opposing Action on Cell Morphogenesis. Cell, Vol. 120, 687–700. Mechaber, W., Marshall, D., Mechaber, R., Jobe, R., Chew, F. (1996). Mapping leaf surface landscapes. PNAS, Vol. 93, 4600-­‐4603. IPCC, 2007: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. Royer D.L. (2000). Stomatal density and stomatal index as indicators of paleoatmospheric CO2 concentration. Review of Palaeobotany and Palynology, Vol. 114, 1-­‐28 Staff, L., Hurd, P., Reale, L., Seoighe, C., Rockwood, A., Gehring, C. (2012). The Hidden Geometries of the Arabidopsis thaliana Epidermis. PLOS ONE, Vol. 7, Issue 9, e43546. Truernit E., Bauby, H., Dubreucq, B., Grandjean, O., Runions, J., Barthélèmy, J., Palauqui, J. (2008). High Resolution Whole-­‐Mount Imaging of Three-­‐
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